A well-known and widely used iterative algorithm to solve (REF ) is the Conjugate Gradient for Least Squares (CGLS) [1]}.
Moreover, by the convergence proprieties of CLGS, \(\lbrace  \phi _k^{\lambda , L} \rbrace _{k\in \mathbb {N}}\)  is a sequence of approximators to \(\Psi ^{\lambda , L}\) . Thus, by Proposition REF , it defines a stabilizer for a neural network \(\Psi _\theta \) . Consequently, we can join either NN or ReNN with this stabilizer, obtaining what we will call StNN and StReNN, respectively. In Algorithms REF  and REF , an implementation of StNN and StReNN can be found.
